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Tobit model used to examine the determinants of the technical inefficiency of hospitals.
Variables used in the estimation of technical efficiency and technical inefficiency factors.
The error term, u iτ, represents production loss due to firm-specific technical inefficiency (unobservable).
If the technical inefficiency does not exist, the estimation becomes a simple OLS estimation.
Inappropriate size of a DMU may sometimes be a cause of technical inefficiency.
The second hypothesis is a technical inefficiency test, with the null hypothesis being no inefficiency effect.
Any deviation from this maximal output is considered as technical inefficiency (Coelli et al. 2005).
If the null hypothesis holds, and then technical inefficiency does not exist.
Obviously, the change of the technical efficiency is related not only to the parameter η which is the rate of change of the industrial technical inefficiency, but also to firm-specific technical inefficiency u iτ.
Villano et al. (2010) estimated technical inefficiency of pistachio cultivators of Kerman Province using Translog production function.
The Ghinda, Nakfa, Adikeyh, Adiquala and Denden hospitals constant returns to scale technical inefficiency was fully attributed to scale inefficiencies.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com